A Novel Quantitative Computer-Assisted Score Can Improve Repeatability in the Estimate of Vascular Calcifications at the Abdominal Aorta

Biochemical Clusters as Substitutes of Bone Biopsies in Kidney Transplant Patients

Bone and mineral metabolism abnormalities are frequent in kidney transplant recipients and have been associated with cardiovascular morbidity. The primary aim of this study was to analyse the association between routine clinically available biochemical evaluation, non-routine histomorphometric bone evaluation, and vascular disease in kidney transplanted patients. A cross-sectional analysis was performed on 69 patients, 1-year after kidney transplantation. Laboratory analysis, radiography of hands and pelvis, bone biopsy, bone densitometry, and coronary CT were performed. One-year post-transplantation, nearly one-third of the patients presented with hypercalcemia, 16% had hypophosphatemia, 39.3% had iPTH levels > 150 pg/mL, 20.3% had BALP levels > 40 U/L, and 26.1% had hypovitaminosis D. Evaluation of extraosseous calcifications revealed low Adragão and Agatston scores. We divided patients into three clusters, according to laboratory results routinely used in clinical practice: hypercalcemia and hyperparathyroidism (Cluster1); hypercalcemia and high BALP levels (Cluster2); hypophosphatemia and vitamin D deficiency (Cluster 3). Patients in clusters 1 and 2 had higher cortical porosity (p = 0.001) and osteoid measurements, although there was no difference in the presence of abnormal mineralization, or low volume. Patients in cluster 2 had a higher BFR/BS (half of the patients in cluster 2 had high bone turnover), and most patients in cluster 1 had low or normal bone turnover. Cluster 3 has no differences in volume, or turnover, but 60% of the patients presented with pre-osteomalacia. All three clusters were associated with high vascular calcifications scores. Vascular calcifications scores were not related to higher bone mineral density. Instead, an association was found between a higher Adragão score and the presence of osteoporosis at the femoral neck (p = 0.008). In conclusion, inferring bone TMV by daily clinical biochemical analysis can be misleading, and bone biopsy is important for assessing both bone turnover and mineralization after kidney transplantation, although hypophosphatemia combined with vitamin D deficiency is associated with abnormal mineralization. The presence of hypercalcemia with high levels of PTH or high levels of BALP, or hypophosphatemia and vitamin D deficiency should remind us to screen vascular calcification status of patients.Clinical Research: ClinicalTrials.gov ID NCT02751099.

Evaluating Osteoporosis in Chronic Kidney Disease: Both Bone Quantity and Quality Matter

Bone strength is determined not only by bone quantity [bone mineral density (BMD)] but also by bone quality, including matrix composition, collagen fiber arrangement, microarchitecture, geometry, mineralization, and bone turnover, among others. These aspects influence elasticity, the load-bearing and repair capacity of bone, and microcrack propagation and are thus key to fractures and their avoidance. In chronic kidney disease (CKD)-associated osteoporosis, factors traditionally associated with a lower bone mass (advanced age or hypogonadism) often coexist with non-traditional factors specific to CKD (uremic toxins or renal osteodystrophy, among others), which will have an impact on bone quality. The gold standard for measuring BMD is dual-energy X-ray absorptiometry, which is widely accepted in the general population and is also capable of predicting fracture risk in CKD. Nevertheless, a significant number of fractures occur in the absence of densitometric World Health Organization (WHO) criteria for osteoporosis, suggesting that methods that also evaluate bone quality need to be considered in order to achieve a comprehensive assessment of fracture risk. The techniques for measuring bone quality are limited by their high cost or invasive nature, which has prevented their implementation in clinical practice. A bone biopsy, high-resolution peripheral quantitative computed tomography, and impact microindentation are some of the methods established to assess bone quality. Herein, we review the current evidence in the literature with the aim of exploring the factors that affect both bone quality and bone quantity in CKD and describing available techniques to assess them.

Establishment and evaluation of a nomogram prediction model for the risk of vascular calcification in stage 5 chronic kidney disease patients

Vascular calcification (VC) is a common complication of chronic kidney disease (CKD) that has a detrimental effect on patients' survival and prognosis. The aim of this study was to develop and validate a practical and reliable prediction model for VC in CKD5 patients. The medical records of 544 CKD5 patients were reviewed retrospectively. Multivariate logistic regression analysis was used to identify the independent risk factors for vascular calcification in patients with CKD5 and then created a nomogram prediction model. The area under the receiver operating characteristic curve (AUC), Hosmer-Lemeshow test, and decision curve analysis (DCA) were used to assess model performance. The patients were split into groups with normal and high serum uric acid levels, and the factors influencing these levels were investigated. Age, BUN, SUA, P and TG were independent risk factors for vascular calcification in CKD5 patients in the modeling group (P < 0.05). In the internal validation, the results of model showed that the AUC was 0.917. No significant divergence between the predicted probability of the nomogram and the actual incidence rate (x2 = 5.406, P = 0.753) was revealed by the calibration plot and HL test, thus confirming that the calibration was satisfactory. The external validation also showed good discrimination (AUC = 0.973). The calibration chart and HL test also demonstrated good consistency. Besides, the correlation analysis of serum uric acid levels in all CKD5 patients revealed that elevated uric acid levels may be related to gender, BUN, P, and TG.

Real-world usage of Chronic Kidney Disease - Mineral Bone Disorder (CKD-MBD) biomarkers in nephrology practices

Background

Chronic kidney disease mineral bone disorder (CKD-MBD) is a condition characterized by alterations of calcium, phosphate, parathyroid hormone (PTH), and fibroblast growth factor 23 (FGF-23) metabolism that in turn promote bone disorders, vascular calcifications, and increase cardiovascular (CV) risk. Nephrologists' awareness of diagnostic, prognostic, and therapeutic tools to manage CKD-MBD plays a primary role in adequately preventing and managing this condition in clinical practice.

Methods

A national survey (composed of 15 closed questions) was launched to inquire about the use of bone biomarkers in the management of CKD-MBD patients by nephrologists and to gain knowledge about the implementation of guideline recommendations in clinical practice.

Results

One hundred and six Italian nephrologists participated in the survey for an overall response rate of about 10%. Nephrologists indicated that the laboratories of their hospitals were able to satisfy request of ionized calcium levels, 105 (99.1%) of both PTH and alkaline phosphatase (ALP), 100 (94.3%) of 25(OH)D, and 61 (57.5%) of 1.25(OH)2D; while most laboratories did not support the requests of biomarkers such as FGF-23 (intact: 88.7% and c-terminal: 93.4%), Klotho (95.3%; soluble form: 97.2%), tartrate-resistant acid phosphatase 5b (TRAP-5b) (92.5%), C-terminal telopeptide (CTX) (71.7%), and pro-collagen type 1 N-terminal pro-peptide (P1NP) (88.7%). As interesting data regarding Italian nephrologists' behavior to start treatment of secondary hyperparathyroidism (sHPT), the majority of clinicians used KDOQI guidelines (n = 55, 51.9%). In contrast, only 40 nephrologists (37.7%) relied on KDIGO guidelines, which recommended referring to values of PTH between two and nine times the upper limit of the normal range.

Conclusion

Results point out a marked heterogeneity in the management of CKD-MBD by clinicians as well as a suboptimal implementation of guidelines in Italian clinical practice.

Automatic Segmentation and Quantification of Abdominal Aortic Calcification in Lateral Lumbar Radiographs Based on Deep-Learning-Based Algorithms

To investigate the performance of deep-learning-based algorithms for the automatic segmentation and quantification of abdominal aortic calcification (AAC) in lateral lumbar radiographs, we retrospectively collected 1359 consecutive lateral lumbar radiographs. The data were randomly divided into model development and hold-out test datasets. The model development dataset was used to develop U-shaped fully convolutional network (U-Net) models to segment the landmarks of vertebrae T12-L5, the aorta, and anterior and posterior aortic calcifications. The AAC lengths were calculated, resulting in an automatic Kauppila score output. The vertebral levels, AAC scores, and AAC severity were obtained from clinical reports and analyzed by an experienced expert (reference standard) and the model. Compared with the reference standard, the U-Net model demonstrated a good performance in predicting the total AAC score in the hold-out test dataset, with a correlation coefficient of 0.97 (p <0.001). The overall accuracy for the AAC severity was 0.77 for the model and 0.74 for the clinical report. Additionally, the Kendall coefficient of concordance of the total AAC score prediction was 0.89 between the model-predicted score and the reference standard, and 0.88 between the structured clinical report and the reference standard. In conclusion, the U-Net-based deep learning approach demonstrated a relatively high model performance in automatically segmenting and quantifying ACC.